Final Presentation: Dynamic Data Collection on the Comprehensive Poverty Assessment in the Rural Area of China
Among all the 17 sustainable development goals of the United Nations until 2030, “End poverty in all its forms everywhere” is the first on the list (Tollefson, 2015). Poverty here entails more than its literal meaning of lack of income or resources for basic livelihood. It is important and necessary to realize that it considers malnutrition, limitation access to education, basic service and infrastructures, even social recognition and discrimination as well. By 2018, almost 8 per cent of the world’s workers and their families lived on less than US$1.90 per person – the internationally agreed poverty line and millions of people lived just beyond this line. The United Nations has clarified what poverty alleviation and ending poverty means to us: “Ensure significant mobilization of resources from a variety of sources, including through enhanced development cooperation, in order to provide adequate and predictable means for developing countries, in particular least developed countries, to implement programs and policies to end poverty in all its dimensions.” (Goal 1: End poverty in all its forms everywhere, 2020) In other words, poverty alleviation can develop the basement of the social development, freedom. Just as Amartya Sen stated in the book Development as Freedom, economic unfreedom can breed social unfreedom, just as social unfreedom can also foster economic unfreedom.(Sen, 1999) Poverty alleviation process is the key to break this vicious circle.
Poverty eradication by China and the Chinese government is under the worldwide spotlight due to the promise of ending absolute poverty by 2020, which is this year and ten years ahead of the deadline set by the United Nations. Back to 2015, there were still 7017 million population under the government’s official extreme poverty line of 2300 RMB ($362.5) per capita annual net income and becoming the targeted population of the poverty alleviation strategy. A new 5-year poverty alleviation plan has been conducted, highlighting the importance of accurate poverty identification, appropriate projects arrangement and accurate effect. According to the goals of China’s government, instead of only caring about the income index, poverty reduction will have been accomplished when standards such as access to food, clothing, compulsory education for children, basic medical treatment and good living conditions are all met. The country had seen a steady decline in the number of impoverished rural residents from nearly 100 million in late 2012 to 16 million by the end of 2018, as shown in data from China’s National Bureau of Statistics. It should reach zero by the end of 2020. (China on its way to end poverty by 2020, 2020) But many people who had barely escaped extreme poverty could be forced back into it by the convergence of COVID-19, conflict, and climate change. All these factors have trapped China and the whole world from economic and social development. The poverty alleviation system in China is rigorous and precise. As the final year of poverty alleviation in 2020, the work plan has been well arranged earlier. But a plan made in advance will always be challenged by unexpected accidents. Due to the outbreak of the Covid-19 epidemic, the process of poverty alleviation passed from the central government to the local government has been disturbed to varying degrees. On one hand, a considerable part of the work had to be postponed again and again, and the pace of poverty alleviation was slowed down; on the other hand, after the outbreak and when the pandemic has been well restrained and controlled, in order to speed up the progress of work in rural areas, the risk that the quality of poverty alleviation might decline. In addition, the people who have been lifted out of poverty will also be impacted due to their vulnerability. The epidemic has brought the risk of returning to poverty and we need to be highly vigilant against this problem. Due to the dual influence of instability and accidental factors from poverty alleviation process, the poverty-stricken population has not yet completely got rid of the problem of vulnerability and their abilities to resist risk and accident are weak.
A dynamic data-basis research will be my answer to the above problems. Traditionally, regional poverty assessment, basically socio-economic development assessment, is based on statistics collected by local governments. GDP is the most popular indicator of economic performance and has been used in a wide range of socio-economic development studies in China. However, there are limits to this type of data, as economic census is usually collected once every five years in China and it takes substantial manpower and generates huge amount of economic costs. It also needs a long period to update existing data and sometimes may become impossible because of various reasons, for example change of local administrative units. It cannot meet special demands also due to the lack of spatial information. And even every different approach used to calculate indicators of living standards for a population has its advantages and disadvantages, and each indicator discerns different characteristics of the population. Consumption data can be highly noisy due to recall error or because expenditures occurred outside the period captured in surveys, but provide a better shorter term concept of poverty Asset-based measures have been regarded as a better proxy for the long-term status of households as they are thought to be more representative of permanent income or long-term control of resources. Besides, especially in the rural area of China, poverty data that is reported to the central government might be flawed or glorified by local insititutions as a presentation of corruption and bureaucratic. So A dynamic dataset becomes urgent and necessary to establish instead of a static one. Data and information related to poverty should be refreshed from time to time in order to maintain the planned process of poverty eradication, which is much more challenging to achieve in the rural area where data collection is inefficient and outdated. The necessity to bring new technologies and data science methodologies into the process of poverty assessment is for the dynamic of data. My Central Resarch Question therefore would like to It will be proposed as: To what extent the remote detection and data science methods can improve the comprehensiveness and reliability of poverty assessment and how can a multidimensional assessing system be established in the rural area of China? This research aims to improve the traditional poverty assessing system by introducing the advanced geospatial data methods including DMSP/OLS night-time light satellite imagery and other comprehensive index.
The further research may focus on the correlations between socio-economic measures and night-time light intensity, access to roads and cities, the entropy of contacts and mobility features help to build up a poverty assessment system which involves various methods instead of a single technique to improve its certainty and accuracy. For instance, remote sensing and geographic information system data (RS data) obtain information like distance to roads and cities, which can reflect access to market and information to a certain degree; and similarly, and mobile operator call detail records (CDR data) like monthly credit consumption on mobile phones and the proportion of people in an area using mobile phones indicate household access to financial resources. Therefore, methods that exploit information from, and correlations between, many different data sources will provide the greatest benefit in understanding the distribution of not only poverty level, but also human living conditions.